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caret (version 5.05.004)

Classification and Regression Training

Description

Misc functions for training and plotting classification and regression models

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Version

Install

install.packages('caret')

Monthly Downloads

230,598

Version

5.05.004

License

GPL-2

Maintainer

Max Kuhn

Last Published

October 11th, 2011

Functions in caret (5.05.004)

BloodBrain

Blood Brain Barrier Data
aucRoc

Compute the area under an ROC curve
bag.default

A General Framework For Bagging
caret-internal

Internal Functions
bagFDA

Bagged FDA
bagEarth

Bagged Earth
cars

Kelly Blue Book resale data for 2005 model year GM cars
avNNet.default

Neural Networks Using Model Averaging
classDist

Compute and predict the distances to class centroids
BoxCoxTrans.default

Box-Cox Transformations
confusionMatrix

Create a confusion matrix
diff.resamples

Inferential Assessments About Model Performance
cox2

COX-2 Activity Data
confusionMatrix.train

Estimate a Resampled Confusion Matrix
GermanCredit

German Credit Data
dhfr

Dihydrofolate Reductase Inhibitors Data
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
dotPlot

Create a dotplot of variable importance values
filterVarImp

Calculation of filter-based variable importance
findCorrelation

Determine highly correlated variables
findLinearCombos

Determine linear combinations in a matrix
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
format.bagEarth

Format 'bagEarth' objects
knn3

k-Nearest Neighbour Classification
icr.formula

Independent Component Regression
predict.train

Extract predictions and class probabilities from train objects
dotplot.diff.resamples

Lattice Functions for Visualizing Resampling Differences
knnreg

k-Nearest Neighbour Regression
xyplot.resamples

Lattice Functions for Visualizing Resampling Results
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
modelLookup

Descriptions Of Models Available in train()
dummyVars

Create A Full Set of Dummy Variables
nearZeroVar

Identification of near zero variance predictors
oil

Fatty acid composition of commercial oils
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
normalize2Reference

Quantile Normalize Columns of a Matrix Based on a Reference Distribution
nullModel

Fit a simple, non-informative model
maxDissim

Maximum Dissimilarity Sampling
panel.needle

Needle Plot Lattice Panel
plot.varImp.train

Plotting variable importance measures
createGrid

Tuning Parameter Grid
plot.train

Plot Method for the train Class
pcaNNet.default

Neural Networks with a Principal Component Step
plotClassProbs

Plot Predicted Probabilities in Classification Models
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
pottery

Pottery from Pre-Classical Sites in Italy
histogram.train

Lattice functions for plotting resampling results
postResample

Calculates performance across resamples
lift

Lift Plot
predictors

List predictors used in the model
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
prcomp.resamples

Principal Components Analysis of Resampling Results
preProcess

Pre-Processing of Predictors
predict.knn3

Predictions from k-Nearest Neighbors
predict.bagEarth

Predicted values based on bagged Earth and FDA models
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
resampleHist

Plot the resampling distribution of the model statistics
print.train

Print Method for the train Class
resampleSummary

Summary of resampled performance estimates
print.confusionMatrix

Print method for confusionMatrix
rfeControl

Controlling the Feature Selection Algorithms
roc

Compute the points for an ROC curve
rfe

Backwards Feature Selection
caretFuncs

Backwards Feature Selection Helper Functions
caretSBF

Selection By Filtering (SBF) Helper Functions
sbfControl

Control Object for Selection By Filtering (SBF)
sbf

Selection By Filtering (SBF)
segmentationData

Cell Body Segmentation
oneSE

Selecting tuning Parameters
sensitivity

Calculate sensitivity, specificity and predictive values
spatialSign

Compute the multivariate spatial sign
tecator

Fat, Water and Protein Content of Meat Samples
trainControl

Control parameters for train
varImp

Calculation of variable importance for regression and classification models
resamples

Collation and Visualization of Resampling Results
summary.bagEarth

Summarize a bagged earth or FDA fit
as.table.confusionMatrix

Save Confusion Table Results
train

Fit Predictive Models over Different Tuning Parameters
lattice.rfe

Lattice functions for plotting resampling results of recursive feature selection
panel.lift2

Lattice Panel Functions for Lift Plots
createDataPartition

Data Splitting functions